User login

Data Catalog Export

Filter through the data catalog entries and export them.
All filtered entries in the view will be downloaded, regardless of page.
Export buttons can be found at the bottom left of the view, and data may be downloaded in CSV, XML, XLS, and TXT form.

We conducted laboratory experiments to test the hypothesis that bedrock erosion is related to grain collisional stresses which scale with shear rate and particle size. We placed granular material in a 56-cm-diameter rotating drum to explore the relationship between erosion of a synthetic bedrock sample and variables such as grain size, shear rate, water content, and bed strength. Grain collisional stresses are estimated as the inertial stress using the product of the squares of particle size and vertical shear rate. Our uniform granular material consisted of 1-mm sand and quartzite river gravel with means of 4, 6, or 10 mm. In 67 experimental runs, the eroded depth of the bed sample varied with inertial stresses in the granular flow to a power less than 1.0 and inversely with the bed strength. The flows tended to slip on smooth boundaries, resulting in higher erosion rates than no-slip cases. We found that lateral wall resistance generated shear across the channel, producing two cells whose widths depended on wall roughness.

We designed a set of flume experiments with a simple, well-defined bed configuration to test our modified sediment transport equation. The experiments were conducted in a small (15 cm wide, 4.5 m long) flume set at a gradient of ten percent. This is the steepest gradient at which fluvial processes have been hypothesized to dominate over debris flow scour and deposition. At this gradient, the influence of the immobile grains on the flow and sediment transport will be relatively large. Thus our experiments should provide a test of sediment transport equations at the limit of their applicability. We maintained a constant slope in our experiments to enable comparisons between all experimental runs. The flume bed consisted of two layers of 30 mm immobile spheres: a closely packed bottom layer (λ/D of 1) and a top layer in which λ/D varied from 1 to 5 in the different runs. (Yager et al., 2007)

Experiments on stochastic avalanching of rice pile as analogue to sediment transport fluctuations. The rice pile is formed in a narrow chamber (width ≈ 2 cm) separated by two flat glass walls (height, width ≈ 30 cm). Rice grains are fed by a custom-built screw feeder controlled by Microsoft VBA script determining rate of rotation of screw feeder (which increases linearly with feed rate of grains). Resulting flux of rice grains out of pile is determined by scale below outlet which records weight every one second. Flux can be determined by differences in scale weight between time steps. A vacuum set to blower mode periodically clears particles from the scale.

Two types of experiments were performed:

Steady feed (constant rate of particle additions to rice pile).

Unsteady feed (sinusoidal, sawtooth, or square wave feeding of particles to rice pile). Different amplitudes and periods of fluctuations among experiments.

Laboratory experiments on initial sediment motion that cross the river to debris-flow sediment-transport transition. Results show that initial sediment motion by river processes requires heightened dimensionless bed shear stress (or critical Shields stress) with increasing channel-bed slope by as much as fivefold the conventional criterion established for lowland rivers.

1. High speed videos (with frame rates ranging from 240-1000 Hz) captured with Phantom High Speed camera. These were intended to capture dynamics of particle collisions and damage propogation.

2. Time lapse photos (with frame rates ranging from 0.1-0.5 Hz) captured with Nikon D5000 (for experiments up to 26Jan2013) and Nikon D5200 (for subsequent experiments). These were intended to explore evolution of the sedimentary bed and particle waiting times through time.

3. Webcam videos (with frame rate of 30 Hz) captured with Logitech webcam. The webcam was set up at the end of the flume, and it is hoped that these videos can help to extract the particle flux.

Not all types of data were collected for all experiments. The details of the individual experiments can be found in the "Notes" files with the associated dates of the experiments.

The "RawData" folders contain the original images from the various cameras (as well as the associated settings files for creating these images). The "ProcessedData" folders contain processed images (cropped and rotated) for the relavant imaging area. They also contain esimates of bed surface elevations and particle centroids determined by image analysis.

The experiments with TimeLapse have been renamed for publication, with the title including the feed rate for the experiments. These are:

S12 -- 16Jul2013

S30 -- combined 2Nov2012 and 13Nov2012

S60 -- 26Jan2013

S90 -- 09Aug2013

S120 -- 31Jul2013

The "ProcessedData" folders also contain the scripts used for processing the data. This has been done by a combination of Fiji (.ijm), Python (.py), and MATLAB (.m) scripts. The '09Aug2013' folder contains the latest scripts for analysis of timelapse experiments. The important ones are:

MODULE_images.py -- a module to be called by other Python scripts when processing the images

process_timelapse.py -- rotates and crops images, then spits them back out into "ProcessedImages" folder as .jpgs. Note: need to look at some raw images to get parameters for processing.

extract_bedsurface.py -- reads in processed images and estimates bed surface elevation (in pixels), spits out text files into "BedSurface" with bed surface elevations. Note, need to look at some processed to get parameters for processing.

particles_FIJI.ijm -- reads in processed images and determines centroids (in pixels) of all particles. Avoids particles on edges of image. Spits out .csv files with these coordinates into "Particles" folder. Note, need to look at some raw images to get parameters for processing.

BedSurfaceMATLABimport.m -- reads in .txt bed surface pixel elevations and converts to bed surface elevations in mm in a single .mat file which can be used for subsequent analysis

ParticlesMATLABimport.m -- reads in .csv particle files and links together into particle trajectories, saving as a single .mat file with all positions trajectories in mm.

See the '26Jan2013' processed data folder for most up-to-date scripts for processing high-speed videos. Probably, it would be better to use some of the scripts described above for these data, but I just haven't had the chance to revisit the high-speed videos in a while. The functions of the scripts are pretty self-explanatory from the titles. The data contained in the folder are:

'V[].mat' contains particle trajectory information. Similar to the "[DATE]_Particles.mat" file described above for time-lapse. 'V[].xls' contains the particle centroids determined by Fiji image analysis. 'V[]_bedsurface.mat' contains bed surface elevations, similar to file described above for time-lapse. 'V[]_movie.mat' and '....tif' contain movies of particle motions as cartoons with hollow spheres and particle identifiers instead of the raw images. Useful for locating particle indices when looking at the trajectory files for analysis.